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Marcel Riedi
Service and Support for Science IT (S3IT)
University of Zurich
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What do we do?

At the Service and Support for Science IT (S3IT) unit we provide support for science in general, and support for life science and medicine in particular. S3IT serves as a partner for both local and national projects to enable competitive research with the advanced use of computational methods and resources. Our team advises groups and projects about data management and data analysis, and cooperates to optimize their specific workflow. S3IT also takes part in national projects and cooperates with similar technology-oriented groups to ensure that its expertise is always up-to-date.

Highlights 2016

Over the course of the year, the team was able to establish successful collaborations with over 130 end-users in 45 research groups from 22 different departments at the University of Zurich. In particular, S3IT launched a platform for integrated data management, workflow management, and data analytics. Such a platform enables the detailed tracking of measured data, as well of the results derived from this data. It also provides users with an easy way to analyze their data through an interactive web portal based on Jupyter.
With regards to infrastructure, in 2016 our team extended the local ScienceCloud infrastructure, which now consists of over 6,000 CPU cores and 2PB of usable storage. Our Hydra system targets use-cases requiring up to 3TB of RAM. In 2016 it was renewed and more than doubled in size. Furthermore, a new GPU cluster system Vesta with a total of 80 GPUs was procured and put into production.

Main publications 2016

  • Hannes L. Röst, Yansheng Liu, Giuseppe D'Agostino, Pierre-Luc Germain, Pedro Navarro, Ben Collins, et al. An automated alignment strategy to obtain comprehensive data matrices in targeted proteomics data. Nature Methods, 2016;13, 777-783.
  • Hannes L. Roest, Timo Sachsenberg, Stephan Aichey, Chris Bielow, Hendrik Weisser, Fabian Aicheler, Sandro Andreotti, et al. OpenMS: A exible open-source software platform for computational mass spectrometry. Nature Methods, 2016;13, 741-748.
  • Stanford NJ, Wolstencroft K, Owen S, Bacall F, Krebs O, Nguyen Q, et al. FAIRDOM: Data and Model Management for all. (in press Nucl Acid Res).

Our research topics: